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Internet technology has flourished in India keeping pace with other developing countries. In keeping pace with this advancement, the Internet of Things (IoT) technology is also spreading in India. Government of India (GOI) has realised IoT's business prospect and published draft policy on IoT in 2015. To achieve a better result, the prospective users are required to be kept aware regarding the prospect of IoT and for this, social media is expected to play a pivotal role. Social media can highlight advantages of IoT and in turn, these advantages would be made known to other potential users through Word of Month (WOM). This would bring in projection of a new business paradigm as contemplated by GOI. The purpose of this paper is to identify the factors affecting actual use of IoT by the potential users of India and to develop a conceptual model. The model has been verified through survey with inputs from 208 participants identified from three metropolitan cities of India. The responses have been quantified through 5-Point Likert scale. The result shows the implication that social media and WOM almost equally influence Indians to use IoT. [ABSTRACT FROM AUTHOR]

This study investigates and compares the continuance intention of full-time business school students and faculty in India and Italy who moved from traditional pedagogy style to the digital classroom due to the COVID-19 pandemic. The study integrates the Expectation Confirmation Model (ECM) and Task-Technology Fit (TTF) to examine their continuance intention. Survey data was collected from 396 business school students and 130 faculty members from India and Italy and analysed using SmartPLS 3 software. The study found that perceived usefulness, satisfaction, and task-technology fit significantly impact the continuance intentions of students and faculty. Multigroup analysis of students indicates that Italian students are more driven by task-technology fit as compared to Indian students in their continuance intention; in comparison, Indian students rely more on gaining experience and knowhow on technology. Finally, the multigroup study of faculty suggests that Italian educators have a comparatively stronger orientation towards the fit between digital classroom technology and a portfolio of related tasks. In comparison, their Indian counterparts rely more on the perceived usefulness of technology. The strength of relationship between task-technology fit and continuance intention is comparatively lower for faculty as compared to students in both countries. Finally, implications for theory and practice are discussed. [ABSTRACT FROM AUTHOR]

Business Management Education in India has shown an upward growth trend in the last couple of decades. Due to the diverse nature of the course, students from diverse academic backgrounds are being admitted to the course. Therefore, differences in students’ abilities and their learning styles have a significant effect on their learning outcomes. Meanwhile, with the development of learning technologies, learners can be provided a more effective learning environment to optimise their learning. The purpose of this study was to develop a model to automatically detect the students’ learning styles from their personal, academic and social media data and make recommendations for students, teachers, educators and administrators for overall improvement of learning outcomes. Data analysis in this research was represented using data collected from post-graduate business management students in India. A 10-fold cross-validation was used to create and test the models. The data were analysed by R and R-Studio. Classification accuracy, Precision, Recall, Kappa, ROC curve and F measure were observed. The results showed that the accuracy of classification by the C4.5 technique had the highest value at 95.7%, and it could be applied to develop Felder-Silverman’s learning style while taking into consideration students’ academic, personal information and social media preferences. [ABSTRACT FROM AUTHOR]